Marqo raises $12.5M Series A for vector search of unstructured data
Ex-Amazon duo's startup tackles 90% of corporate data with vector search
Ex-Amazon co-founders Jesse Clark (CTO, 40) and Tom Hamer (CEO, 27) are tackling one of enterprise AI's biggest bottlenecks: unstructured data. Their startup Marqo just closed a $12.5M Series A round led by Lightspeed Venture Partners, with participation from Blackbird Ventures and January Capital. The company has now raised $17.8M total and is moving its headquarters from London and Melbourne to San Francisco to fuel commercial expansion.
Marqo's platform applies vector search—a machine learning technique that transforms data into numerical vectors—to enable fast, context-aware retrieval from messy corporate datasets like emails, contracts, and logs (which IDC estimates comprise ~90% of enterprise data). The managed cloud service targets industries like healthcare and e-commerce, enabling use cases such as personalized product recommendations and sentiment analysis. "Mastering unstructured data will be key to success in the AI race," Clark said, positioning Marqo as an infrastructure layer for enterprises that want to harness their hidden information assets.
- Raised $12.5M Series A led by Lightspeed, with $17.8M total funding to date
- Uses vector search (ML-based) to index unstructured data like emails and contracts, which represents ~90% of corporate data
- Founded by ex-Amazon engineers Jesse Clark and Tom Hamer; relocating HQ to San Francisco
Why It Matters
Unlocking unstructured data is critical for enterprise AI, enabling better personalization, analytics, and RAG workflows.